{"id":"https://openalex.org/W3156271283","doi":"https://doi.org/10.1145/3442381.3450132","title":"Unsupervised Semantic Association Learning with Latent Label Inference","display_name":"Unsupervised Semantic Association Learning with Latent Label Inference","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3156271283","doi":"https://doi.org/10.1145/3442381.3450132","mag":"3156271283"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3450132","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3450132","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3450132","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103114439","display_name":"Yanzhao Zhang","orcid":"https://orcid.org/0000-0003-2894-4727"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanzhao Zhang","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027015677","display_name":"Richong Zhang","orcid":"https://orcid.org/0000-0002-1207-0300"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richong Zhang","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101740394","display_name":"Jaein Kim","orcid":"https://orcid.org/0000-0001-7148-4346"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jaein Kim","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104561219","display_name":"Xudong Liu","orcid":"https://orcid.org/0009-0007-8865-3055"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Liu","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004793184","display_name":"Yongyi Mao","orcid":"https://orcid.org/0000-0001-5298-5778"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yongyi Mao","raw_affiliation_strings":["University of Ottawa, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Ottawa, Canada","institution_ids":["https://openalex.org/I153718931"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4010","last_page":"4019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8474228382110596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7756034731864929},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.709501326084137},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6679151058197021},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5882031917572021},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5438795685768127},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5208387970924377},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5154026746749878},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49297404289245605},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46050024032592773},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44366681575775146},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.4355143904685974},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4210951626300812},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.41626057028770447},{"id":"https://openalex.org/keywords/latent-variable-model","display_name":"Latent variable model","score":0.41434311866760254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8474228382110596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7756034731864929},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.709501326084137},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6679151058197021},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5882031917572021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5438795685768127},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5208387970924377},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5154026746749878},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49297404289245605},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46050024032592773},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44366681575775146},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.4355143904685974},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4210951626300812},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.41626057028770447},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.41434311866760254},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3442381.3450132","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3450132","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3442381.3450132","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3450132","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1981159181","https://openalex.org/W2049633694","https://openalex.org/W2101746535","https://openalex.org/W2127289991","https://openalex.org/W2130237711","https://openalex.org/W2251202616","https://openalex.org/W2251818205","https://openalex.org/W2468484304","https://openalex.org/W2518202280","https://openalex.org/W2539338396","https://openalex.org/W2539671052","https://openalex.org/W2610935556","https://openalex.org/W2740782137","https://openalex.org/W2747329762","https://openalex.org/W2750779823","https://openalex.org/W2752172973","https://openalex.org/W2760753016","https://openalex.org/W2774343269","https://openalex.org/W2799042618","https://openalex.org/W2887005207","https://openalex.org/W2891031945","https://openalex.org/W2891177506","https://openalex.org/W2892202790","https://openalex.org/W2892737606","https://openalex.org/W2915240437","https://openalex.org/W2922386288","https://openalex.org/W2945127593","https://openalex.org/W2945329331","https://openalex.org/W2945465473","https://openalex.org/W2948947170","https://openalex.org/W2953075226","https://openalex.org/W2962739339","https://openalex.org/W2963001778","https://openalex.org/W2963511204","https://openalex.org/W2964245140","https://openalex.org/W2965311366","https://openalex.org/W2970641574","https://openalex.org/W2970662235","https://openalex.org/W2970773744","https://openalex.org/W2970971581","https://openalex.org/W2984469754","https://openalex.org/W3038005645","https://openalex.org/W3099446234","https://openalex.org/W4239019441","https://openalex.org/W4252076394"],"related_works":["https://openalex.org/W2242083226","https://openalex.org/W1603253275","https://openalex.org/W1514645777","https://openalex.org/W2884410131","https://openalex.org/W111011176","https://openalex.org/W2138996412","https://openalex.org/W2906932471","https://openalex.org/W2763292376","https://openalex.org/W2097596242","https://openalex.org/W2270140793"],"abstract_inverted_index":{"In":[0],"this":[1,32],"paper,":[2],"we":[3,23],"unify":[4],"a":[5,19,47,63],"diverse":[6],"set":[7],"of":[8,31,115],"learning":[9,28,61,82],"tasks":[10,110],"in":[11,70],"NLP,":[12],"semantic":[13,26,107],"retrieval":[14,108],"and":[15,41,86,95,103,111],"related":[16],"areas,":[17],"under":[18,58,92],"common":[20],"umbrella,":[21],"which":[22],"call":[24],"unsupervised":[25],"association":[27],"(USAL).":[29],"Examples":[30],"generic":[33],"task":[34],"include":[35],"word":[36],"sense":[37],"disambiguation,":[38],"answer":[39],"selection":[40],"question":[42],"retrieval.":[43],"We":[44,99],"then":[45,79],"present":[46],"novel":[48],"modeling":[49],"framework":[50,56],"to":[51,105],"tackle":[52],"such":[53],"tasks.":[54],"The":[55],"introduces,":[57],"the":[59,67,71,83,88,101,112,116],"deep":[60,84],"paradigm,":[62],"latent":[64,89],"label":[65],"indexing":[66],"true":[68],"target":[69,73],"candidate":[72],"set.":[74],"An":[75],"EM":[76],"algorithm":[77,104],"is":[78,119],"developed":[80],"for":[81],"model":[85,102],"inferring":[87],"variables,":[90],"principled":[91],"variational":[93],"techniques":[94],"noise":[96],"contrastive":[97],"estimation.":[98],"apply":[100],"several":[106],"benchmark":[109],"superior":[113],"performance":[114],"proposed":[117],"approach":[118],"demonstrated":[120],"via":[121],"empirical":[122],"studies.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
